Triple
T10331384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tavush Province |
E242881
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Noyemberyan |
E242887
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Noyemberyan | Statement: [Tavush Province, hasCity, Noyemberyan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Noyemberyan Context triple: [Tavush Province, hasCity, Noyemberyan]
-
A.
Noyemberyan
chosen
Noyemberyan is a small town in northeastern Armenia known for its mountainous surroundings and proximity to the Georgian border.
-
B.
Noyabrsk
Noyabrsk is a major oil and gas industry city in northern Russia, located in the Yamalo-Nenets region of Western Siberia.
-
C.
Noyyal
Noyyal is a river in the Indian state of Tamil Nadu, known for flowing through the Coimbatore region and contributing to the Kaveri river system.
-
D.
Oktyabrsk
Oktyabrsk is a small industrial city in Russia located on the Volga River within Samara Oblast.
-
E.
Ninalla
Ninalla was the wife of Gudea, the prominent ruler (ensi) of the Sumerian city-state of Lagash in the late 3rd millennium BCE.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7fcaf4c8190bdcfcb953d88ea2f |
completed | April 7, 2026, 10:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7504d49e88190b2739522f3ead702 |
completed | April 9, 2026, 7:07 a.m. |
Created at: April 6, 2026, 11:52 a.m.